def create_apollo_info_file(data_path, save_path=None, relative_path=True):
#找train.txt val.txt...，拿里面的ids来用
imageset_folder = Path(__file__).resolve().parent / "ImageSets"
train_img_ids = _read_imageset_file(str(imageset_folder / "train.txt"))
val_img_ids = _read_imageset_file(str(imageset_folder / "val.txt"))
test_img_ids = _read_imageset_file(str(imageset_folder / "test.txt"))
print("Generate info. this may take several minutes.")
#找存哪里
if save_path is None:
save_path = Path(data_path)
else:
save_path = Path(save_path)
#用get_kitti_image_info把数据做成pkl
kitti_infos_train = kitti.get_kitti_image_info(data_path,
training=True,
velodyne=True,
calib=True,
image_ids=train_img_ids,
relative_path=relative_path)
#计算gt里的点数量
_calculate_num_points_in_gt(data_path, kitti_infos_train, relative_path)
#用刚刚写的存的点决定存哪里，把它存进去
filename = save_path / 'kitti_infos_train.pkl'
print(f"Kitti info train file is saved to {filename}")
with open(filename, 'wb') as f:
pickle.dump(kitti_infos_train, f)
kitti_infos_val = kitti.get_kitti_image_info(data_path,
training=True,
velodyne=True,
calib=True,
image_ids=val_img_ids,
relative_path=relative_path)
_calculate_num_points_in_gt(data_path, kitti_infos_val, relative_path)
filename = save_path / 'kitti_infos_val.pkl'
print(f"Kitti info val file is saved to {filename}")
with open(filename, 'wb') as f:
pickle.dump(kitti_infos_val, f)
filename = save_path / 'kitti_infos_trainval.pkl'
print(f"Kitti info trainval file is saved to {filename}")
with open(filename, 'wb') as f:
pickle.dump(kitti_infos_train + kitti_infos_val, f)
kitti_infos_test = kitti.get_kitti_image_info(data_path,
training=False,
label_info=False,
velodyne=True,
calib=True,
image_ids=test_img_ids,
relative_path=relative_path)
filename = save_path / 'kitti_infos_test.pkl'
print(f"Kitti info test file is saved to {filename}")
with open(filename, 'wb') as f:
pickle.dump(kitti_infos_test, f)
def create_kitti_info_file0(data_path,
save_path=None,
create_trainval=False,
relative_path=True):
train_img_ids = _read_imageset_file("./data/ImageSets/train0.txt")
val_img_ids = _read_imageset_file("./data/ImageSets/val0.txt")
#trainval_img_ids = _read_imageset_file("./data/ImageSets/trainval.txt")
#test_img_ids = _read_imageset_file("./data/ImageSets/test.txt")
#test_img_ids = _read_imageset_file("./data/ImageSets/test2.txt")
print("Generate info. this may take several minutes.")
if save_path is None:
save_path = pathlib.Path(data_path)
else:
save_path = pathlib.Path(save_path)
kitti_infos_train = kitti.get_kitti_image_info(
data_path,
training=True,
velodyne=True,
calib=True,
image_ids=train_img_ids,
relative_path=relative_path)
_calculate_num_points_in_gt(data_path, kitti_infos_train, relative_path)
filename = save_path / 'kitti_infos_train.pkl'
print(f"Kitti info train file is saved to {filename}")
with open(filename, 'wb') as f:
pickle.dump(kitti_infos_train, f)
kitti_infos_val = kitti.get_kitti_image_info(
data_path,
training=True,
velodyne=True,
calib=True,
image_ids=val_img_ids,
relative_path=relative_path)
_calculate_num_points_in_gt(data_path, kitti_infos_val, relative_path)
filename = save_path / 'kitti_infos_val.pkl'
print(f"Kitti info val file is saved to {filename}")
with open(filename, 'wb') as f:
pickle.dump(kitti_infos_val, f)
"""
if create_trainval:
kitti_infos_trainval = kitti.get_kitti_image_info(
data_path,
training=True,
velodyne=True,
calib=True,
image_ids=trainval_img_ids,
relative_path=relative_path)
filename = save_path / 'kitti_infos_trainval.pkl'
print(f"Kitti info trainval file is saved to {filename}")
with open(filename, 'wb') as f:
pickle.dump(kitti_infos_trainval, f)
"""
filename = save_path / 'kitti_infos_trainval.pkl'
print(f"Kitti info trainval file is saved to {filename}")
with open(filename, 'wb') as f:
pickle.dump(kitti_infos_train + kitti_infos_val, f)
def create_kitti_info_file(data_path,
save_path=None,
create_trainval=False,
relative_path=True):
dir_path = os.path.dirname(os.path.realpath(__file__))
train_img_ids = _read_imageset_file(dir_path + "/data/ImageSets/train.txt")
val_img_ids = _read_imageset_file(dir_path + "/data/ImageSets/val.txt")
trainval_img_ids = _read_imageset_file(dir_path +
"/data/ImageSets/trainval.txt")
test_img_ids = _read_imageset_file(dir_path + "/data/ImageSets/test.txt")
print("Generate info. this may take several minutes.")
if save_path is None:
save_path = pathlib.Path(data_path)
else:
save_path = pathlib.Path(save_path)
kitti_infos_train = kitti.get_kitti_image_info(data_path,
training=True,
velodyne=True,
calib=True,
image_ids=train_img_ids,
relative_path=relative_path)
_calculate_num_points_in_gt(data_path, kitti_infos_train, relative_path)
filename = save_path / 'kitti_infos_train.pkl'
print(f"Kitti info train file is saved to {filename}")
with open(filename, 'wb') as f:
pickle.dump(kitti_infos_train, f)
kitti_infos_val = kitti.get_kitti_image_info(data_path,
training=True,
velodyne=True,
calib=True,
image_ids=val_img_ids,
relative_path=relative_path)
_calculate_num_points_in_gt(data_path, kitti_infos_val, relative_path)
filename = save_path / 'kitti_infos_val.pkl'
print(f"Kitti info val file is saved to {filename}")
with open(filename, 'wb') as f:
pickle.dump(kitti_infos_val, f)
filename = save_path / 'kitti_infos_trainval.pkl'
print(f"Kitti info trainval file is saved to {filename}")
with open(filename, 'wb') as f:
pickle.dump(kitti_infos_train + kitti_infos_val, f)
kitti_infos_test = kitti.get_kitti_image_info(data_path,
training=False,
label_info=False,
velodyne=True,
calib=True,
image_ids=test_img_ids,
relative_path=relative_path)
filename = save_path / 'kitti_infos_test.pkl'
print(f"Kitti info test file is saved to {filename}")
#print(kitti_infos_test)
with open(filename, 'wb') as f:
pickle.dump(kitti_infos_test, f)
def create_kitti_info_file(data_path,
save_path=None,
create_trainval=False,
relative_path=True):
train_img_ids = list(range(0, 4533))
val_img_ids = list(range(0, 750))
trainval_img_ids = list(range(0, 7480)) # only kitti
test_img_ids = list(range(0, 7517)) # only kitti
print("Generate info. this may take several minutes.")
if save_path is None:
save_path = pathlib.Path(data_path)
else:
save_path = pathlib.Path(save_path)
# get all the annos from the file
kitti_infos_train = kitti.get_kitti_image_info(data_path,
training=True,
velodyne=True,
calib=True,
image_ids=train_img_ids,
relative_path=relative_path)
# calculate the number of points in the pointcloud which fall into each gt box
_calculate_num_points_in_gt(data_path, kitti_infos_train, relative_path)
# ------------------------------------------------------------------------------------------------------
# save pc infos
# ------------------------------------------------------------------------------------------------------
filename = save_path / 'kitti_infos_train.pkl'
print(f"Kitti info train file is saved to {filename}")
with open(filename, 'wb') as f:
pickle.dump(kitti_infos_train, f, 2)
# do the same for training set
kitti_infos_val = kitti.get_kitti_image_info(data_path,
training=False,
velodyne=True,
calib=True,
image_ids=val_img_ids,
relative_path=relative_path)
_calculate_num_points_in_gt(data_path, kitti_infos_val, relative_path)
filename = save_path / 'kitti_infos_val.pkl'
print(f"Kitti info val file is saved to {filename}")
with open(filename, 'wb') as f:
pickle.dump(kitti_infos_val, f, 2)
# ------------------------------------------------------------------------------------------------------
# old KITTI stuff
# ------------------------------------------------------------------------------------------------------
"""
def create_kitti_info_file_tracking(data_path,
sequence,
save_path=None,
relative_path=True):
train_img_ids = sorted(
int(p.stem) for p in ((Path(data_path) / "training" / "velodyne" /
sequence).glob("*")))
print("Generate info. this may take several minutes.")
if save_path is None:
save_path = Path(data_path)
else:
save_path = Path(save_path)
kitti_infos_train = kitti.get_kitti_image_info(
data_path,
training=True,
label_info=
False, # TODO(brendan): Not handling reading labels for tracking right now.
velodyne=True,
calib=True,
image_ids=train_img_ids,
relative_path=relative_path,
sequence=sequence)
# TODO(brendan): seems to just adjust annos, which I'm not setting for tracking right now.
# _calculate_num_points_in_gt(data_path, kitti_infos_train, relative_path)
filename = save_path / f'kitti_infos_train{sequence}.pkl'
print(f"Kitti info train file is saved to {filename}")
with open(filename, 'wb') as f:
pickle.dump(kitti_infos_train, f)
def create_kitti_tracking_info_file(data_path, save_path=None, relative_path=True):
imageset_folder = Path(__file__).resolve().parent / "ImageSets"
train_img_ids = _read_tracking_imageset_file(str(imageset_folder / "tracking_training_info_v4.txt"))
val_img_ids = _read_tracking_imageset_file(str(imageset_folder / "tracking_val_info_v4.txt"))
# NO test set from kitti tracking
# test_img_ids = _read_imageset_file(str(imageset_folder / "test_tracking.txt"))
print("Number of kitti tracking training data:{}".format(len(train_img_ids)))
print("Number of kitti tracking val data:{}".format(len(val_img_ids)))
print("Generate info. this may take several minutes.")
if save_path is None:
save_path = Path(data_path)
else:
save_path = Path(save_path)
kitti_infos_train = kitti.get_kitti_image_info(
data_path,
training=True,
tracking=True,
velodyne=True,
calib=True,
num_worker=8, # debug only
image_ids=train_img_ids,
relative_path=relative_path)
_calculate_num_points_in_gt(data_path, kitti_infos_train, relative_path)
filename = save_path / 'kitti_infos_train.pkl'
print(f"Kitti info train file is saved to {filename}")
with open(filename, 'wb') as f:
pickle.dump(kitti_infos_train, f)
kitti_infos_val = kitti.get_kitti_image_info(
data_path,
training=True,
tracking=True,
velodyne=True,
calib=True,
image_ids=val_img_ids,
relative_path=relative_path)
_calculate_num_points_in_gt(data_path, kitti_infos_val, relative_path)
filename = save_path / 'kitti_infos_val.pkl'
print(f"Kitti info val file is saved to {filename}")
with open(filename, 'wb') as f:
pickle.dump(kitti_infos_val, f)
filename = save_path / 'kitti_infos_trainval.pkl'
print(f"Kitti info trainval file is saved to {filename}")
with open(filename, 'wb') as f:
pickle.dump(kitti_infos_train + kitti_infos_val, f)
def initialize(self):
image_infos = get_kitti_image_info(self.data_path,
training=True,
label_info=False,
calib=True,
image_ids=[self.calib_idx])
self.calib_info = image_infos[0]
self._build()
self._restore()
def create_kitti_info_file_only_test(data_path,
save_path=None,
create_trainval=False,
relative_path=True):
test_img_ids = _read_imageset_file("./data/ImageSets/test.txt")
print("Generate info. this may take several minutes.")
if save_path is None:
save_path = pathlib.Path(data_path)
else:
save_path = pathlib.Path(save_path)
kitti_infos_test = kitti.get_kitti_image_info(data_path,
training=False,
label_info=False,
velodyne=True,
calib=True,
image_ids=test_img_ids,
relative_path=relative_path)
filename = save_path / 'kitti_infos_test.pkl'
print(f"Kitti info test file is saved to {filename}")
with open(filename, 'wb') as f:
pickle.dump(kitti_infos_test, f)
def create_kitti_info_file(data_path,
save_path=None,
create_trainval=False,
relative_path=True,
scene_num=None):
# train_img_ids = _read_imageset_file("./data/ImageSets/train.txt")
# val_img_ids = _read_imageset_file("./data/ImageSets/val.txt")
# trainval_img_ids = _read_imageset_file("./data/ImageSets/trainval.txt")
# scene_num ="0104"
if scene_num is not None:
test_img_ids = _read_imageset_file(
"/home/spalab/jhyoo/dataset/KITTI_raw/2011_09_26_drive_" +
scene_num + "_sync/testing/test.txt")
else:
import pdb
pdb.set_trace()
temp = 1
print("Generate info. this may take several minutes.")
if save_path is None:
save_path = pathlib.Path(data_path)
else:
save_path = pathlib.Path(save_path)
# kitti_infos_train = kitti.get_kitti_image_info(
# data_path,
# training=True,
# velodyne=True,
# calib=True,
# image_ids=train_img_ids,
# relative_path=relative_path)
# _calculate_num_points_in_gt(data_path, kitti_infos_train, relative_path)
# filename = save_path / 'kitti_infos_train.pkl'
# print(f"Kitti info train file is saved to {filename}")
# with open(filename, 'wb') as f:
# pickle.dump(kitti_infos_train, f)
# kitti_infos_val = kitti.get_kitti_image_info(
# data_path,
# training=True,
# velodyne=True,
# calib=True,
# image_ids=val_img_ids,
# relative_path=relative_path)
# _calculate_num_points_in_gt(data_path, kitti_infos_val, relative_path)
# filename = save_path / 'kitti_infos_val.pkl'
# print(f"Kitti info val file is saved to {filename}")
# with open(filename, 'wb') as f:
# pickle.dump(kitti_infos_val, f)
# """
# if create_trainval:
# kitti_infos_trainval = kitti.get_kitti_image_info(
# data_path,
# training=True,
# velodyne=True,
# calib=True,
# image_ids=trainval_img_ids,
# relative_path=relative_path)
# filename = save_path / 'kitti_infos_trainval.pkl'
# print(f"Kitti info trainval file is saved to {filename}")
# with open(filename, 'wb') as f:
# pickle.dump(kitti_infos_trainval, f)
# """
# filename = save_path / 'kitti_infos_trainval.pkl'
# print(f"Kitti info trainval file is saved to {filename}")
# with open(filename, 'wb') as f:
# pickle.dump(kitti_infos_train + kitti_infos_val, f)
kitti_infos_test = kitti.get_kitti_image_info(data_path,
training=False,
label_info=False,
velodyne=True,
calib=True,
image_ids=test_img_ids,
relative_path=relative_path)
f_name = 'kitti_infos_test_' + scene_num + '.pkl'
filename = save_path / f_name
print(f"Kitti info test file is saved to {filename}")
with open(filename, 'wb') as f:
pickle.dump(kitti_infos_test, f)
def create_kitti_info_file(data_path,
save_path=None,
create_trainval=False,
relative_path=True):
train_img_ids = _read_imageset_file("./data/ImageSets/train.txt")
val_img_ids = _read_imageset_file("./data/ImageSets/val.txt")
trainval_img_ids = _read_imageset_file("./data/ImageSets/trainval.txt")
test_img_ids = _read_imageset_file("./data/ImageSets/test.txt")
print("Generate info. this may take several minutes.")
if save_path is None:
save_path = pathlib.Path(data_path)
else:
save_path = pathlib.Path(save_path)
try:
kitti_infos_train = kitti.get_kitti_image_info(
data_path,
training=True,
velodyne=True,
calib=True,
image_ids=train_img_ids,
relative_path=relative_path)
except Exception as e:
print('Got exception: {}'.format(e))
kitti_infos_train = [i for i in kitti_infos_train if i is not None]
print('Found all {} valid train infos.'.format(len(kitti_infos_train)))
_calculate_num_points_in_gt(data_path, kitti_infos_train, relative_path)
filename = save_path / 'kitti_infos_train.pkl'
print(f"Kitti info train file is saved to {filename}")
with open(filename, 'wb') as f:
pickle.dump(kitti_infos_train, f)
kitti_infos_val = kitti.get_kitti_image_info(data_path,
training=True,
velodyne=True,
calib=True,
image_ids=val_img_ids,
relative_path=relative_path)
kitti_infos_val = [i for i in kitti_infos_val if i is not None]
print('Found all {} valid test infos.'.format(len(kitti_infos_val)))
_calculate_num_points_in_gt(data_path, kitti_infos_val, relative_path)
filename = save_path / 'kitti_infos_val.pkl'
print(f"Kitti info val file is saved to {filename}")
with open(filename, 'wb') as f:
pickle.dump(kitti_infos_val, f)
"""
if create_trainval:
kitti_infos_trainval = kitti.get_kitti_image_info(
data_path,
training=True,
velodyne=True,
calib=True,
image_ids=trainval_img_ids,
relative_path=relative_path)
filename = save_path / 'kitti_infos_trainval.pkl'
print(f"Kitti info trainval file is saved to {filename}")
with open(filename, 'wb') as f:
pickle.dump(kitti_infos_trainval, f)
"""
filename = save_path / 'kitti_infos_trainval.pkl'
print(f"Kitti info trainval file is saved to {filename}")
with open(filename, 'wb') as f:
pickle.dump(kitti_infos_train + kitti_infos_val, f)
kitti_infos_test = kitti.get_kitti_image_info(data_path,
training=False,
label_info=False,
velodyne=True,
calib=True,
image_ids=test_img_ids,
relative_path=relative_path)
kitti_infos_test = [i for i in kitti_infos_test if i is not None]
print('Found all {} valid test infos.'.format(len(kitti_infos_test)))
filename = save_path / 'kitti_infos_test.pkl'
print(f"Kitti info test file is saved to {filename}")
with open(filename, 'wb') as f:
pickle.dump(kitti_infos_test, f)
def create_kitti_info_file(data_path,
save_path=None,
create_trainval=False,
relative_path=True):
# Read all the lines in the already stored names of image files
train_img_ids = _read_imageset_file("./data/ImageSets/train.txt")
val_img_ids = _read_imageset_file("./data/ImageSets/val.txt")
# trainval_img_ids = _read_imageset_file("./data/ImageSets/trainval.txt") # FIXME: Not sure what is trainval, simply a sum of train and val sets?
test_img_ids = _read_imageset_file("./data/ImageSets/test.txt")
print("Generate info. this may take several minutes.")
if save_path is None:
save_path = pathlib.Path(data_path)
else:
save_path = pathlib.Path(save_path)
# Store train data info
kitti_infos_train = kitti.get_kitti_image_info(
data_path,
training=True,
velodyne=True,
calib=True,
image_ids=train_img_ids,
relative_path=relative_path
) # NOTE: Get all useful info about each image such as TF, calibration, path to file, image shape
_calculate_num_points_in_gt(
data_path, kitti_infos_train, relative_path
) # Add num of points in ground-truth using call by reference approach
filename = save_path / 'kitti_infos_train.pkl'
print(f"Kitti info train file is saved to {filename}")
with open(filename, 'wb') as f:
pickle.dump(kitti_infos_train, f)
# Store val data info
kitti_infos_val = kitti.get_kitti_image_info(data_path,
training=True,
velodyne=True,
calib=True,
image_ids=val_img_ids,
relative_path=relative_path)
_calculate_num_points_in_gt(data_path, kitti_infos_val, relative_path)
filename = save_path / 'kitti_infos_val.pkl'
print(f"Kitti info val file is saved to {filename}")
with open(filename, 'wb') as f:
pickle.dump(kitti_infos_val, f)
"""
if create_trainval:
kitti_infos_trainval = kitti.get_kitti_image_info(
data_path,
training=True,
velodyne=True,
calib=True,
image_ids=trainval_img_ids,
relative_path=relative_path)
filename = save_path / 'kitti_infos_trainval.pkl'
print(f"Kitti info trainval file is saved to {filename}")
with open(filename, 'wb') as f:
pickle.dump(kitti_infos_trainval, f)
"""
filename = save_path / 'kitti_infos_trainval.pkl'
print(f"Kitti info trainval file is saved to {filename}")
with open(filename, 'wb') as f:
pickle.dump(kitti_infos_train + kitti_infos_val, f)
# Store test data info
kitti_infos_test = kitti.get_kitti_image_info(data_path,
training=False,
label_info=False,
velodyne=True,
calib=True,
image_ids=test_img_ids,
relative_path=relative_path)
filename = save_path / 'kitti_infos_test.pkl'
print(f"Kitti info test file is saved to {filename}")
with open(filename, 'wb') as f:
pickle.dump(kitti_infos_test, f)
